As a result of the fact that judgments of non-native speech are closely tied to social biases, oral proficiency ratings are susceptible to error because of rater background and social attitudes. In the present study we seek first to estimate the variance attributable to rater background and attitudinal variables on novice raters' assessments of L2…

In this paper, we describe and evaluate two state-of-the-art systems for identifying and correcting writing errors involving English articles and prepositions. Criterion[superscript SM], developed by Educational Testing Service, and "ESL Assistant", developed by Microsoft Research, both use machine learning techniques to build models of article…

This study used a mixed methods research approach to examine how native English-speaking (NS) and non-native English-speaking (NNS) teachers assess students' oral English performance. The evaluation behaviors of two groups of teachers (12 Canadian NS teachers and 12 Korean NNS teachers) were compared with regard to internal consistency, severity,…